The promise of pharmacogenomics - identification of the right dose of the right drug the first time for everyone - has yet to be fully realized in part because we lack a complete understanding of the mechanisms underlying drug response variability. Recent studies suggest that microRNAs (miRs) - small noncoding RNAs that regulate gene expression post-transcriptionally - could be an important determinant of interindividual variability in drug metabolism and disposition. Here we propose to use a variety of novel approaches to identify miRs that are responsible for drug metabolizing enzyme variability. The focus of the application will be the UDP- glucuronosyltransferase (UGT) 1A enzymes that are critical to the elimination of many clinically important drugs with a narrow therapeutic index. Importantly, al 9 UGT1A enzymes (out of 18 total human UGTs) are encoded by spliced mRNAs that share an identical 3'-untranslated region (UTR). Although we have evidence that these enzymes are co-regulated by a post-transcriptional mechanism, virtually nothing is known regarding the role of miRs in UGT1A expression. Our overarching hypothesis is that specific miRs regulate UGT1A gene expression through the conserved UGT1A-3'-UTR mRNA region and/or indirectly by modulating regulatory transcription factor levels. To test this hypothesis, th following specific aims are proposed. In Aim 1 candidate miRs associated with UGT1A glucuronidation will be identified by multiple independent approaches, including bioinformatics, functional genomics screen, and whole genome (miR-transcriptome) association studies. The novel functional genomics screen we propose enables rapid identification of miRs that suppress a fluorescent- tagged miR 3'-UTR reporter from a pooled lentivirus library of all known human miRs. This method should have broad application outside of our field enabling a cost-effective rapid approach to describing of the miR interactome. The reference UGT1A-3'-UTR allele will be evaluated as well as the major variant (*1b) associated with decreased bilirubin glucuronidation in vivo. miRs that are overexpressed in human liver bank samples with a low UGT1A activity and translational efficiency phenotype will also be identified by miR transcriptomics (arrays and Next gen small RNA-seq). In Aim 2 we wil confirm the functional impact of candidate miRs on UGT1A glucuronidation through overexpression (lenti-miRs) and knockdown (lenti- antagomiRs) of candidate miRs in human model cell lines and primary hepatocytes. In Aim 3 we will determine the mechanism of UGT1A regulation by functional miRs through use of UGT1A-3'UTR luciferase-reporter constructs and through studying effects of miR overexpression and knockdown in model cell lines and primary human hepatocytes on specific candidate transcription factor proteins (PXR and HNF1) as well as the entire proteome (iTRAQ LC-MS/MS method). This work will ultimately lead to development of validated predictive biomarkers (miR-associated polymorphisms and/or miR levels in blood) that would be incorporated into the pharmacogenetic algorithms currently being developed to guide dosing of low therapeutic index drugs.